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Learning Translation-Based Knowledge Graph Embeddings by N-Pair Translation Loss
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In: Applied Sciences ; Volume 10 ; Issue 11 (2020)
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Aspect-Based Sentiment Analysis Using Aspect Map
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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Abstractive Sentence Compression with Event Attention
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In: Applied Sciences ; Volume 9 ; Issue 19 (2019)
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A Multitask-Based Neural Machine Translation Model with Part-of-Speech Tags Integration for Arabic Dialects
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In: Applied Sciences ; Volume 8 ; Issue 12 (2018)
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A Sentence-To-Sentence Relation Network For Recognizing Textual Entailment ...
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A Sentence-To-Sentence Relation Network For Recognizing Textual Entailment ...
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Target Concept Selection By Property Overlap In Ontology Population ...
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Target Concept Selection By Property Overlap In Ontology Population ...
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9 |
Determining The Gender Of Korean Names For Pronoun Generation ...
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Determining The Gender Of Korean Names For Pronoun Generation ...
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Resolving Dependency Ambiguity Of Subordinate Clauses Using Support Vector Machines ...
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Resolving Dependency Ambiguity Of Subordinate Clauses Using Support Vector Machines ...
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Abstract:
In this paper, we propose a method of resolving dependency ambiguities of Korean subordinate clauses based on Support Vector Machines (SVMs). Dependency analysis of clauses is well known to be one of the most difficult tasks in parsing sentences, especially in Korean. In order to solve this problem, we assume that the dependency relation of Korean subordinate clauses is the dependency relation among verb phrase, verb and endings in the clauses. As a result, this problem is represented as a binary classification task. In order to apply SVMs to this problem, we selected two kinds of features: static and dynamic features. The experimental results on STEP2000 corpus show that our system achieves the accuracy of 73.5%. ... : {"references": ["K.-J. Seo, A Korean language parser using syntactic dependency relations between word-phrases, M.S. Thesis, KAIST, 1993.", "S.-B. Park and B.-T. Zhang, ''Text Chunking by Combining Hand-Crafted Rules and Memory-Based Learning,'' In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics, pp. 497--504, 2003.", "H.-P. Shin, ''Maximally Efficient Syntactic Parsing with Minimal Resources,'' In Proceedings of the Conference on Hangul and Korean Language Information Processing, pp. 242-244, 1999. (In Korean)", "H.-J. Lee, S.-B. Park, S.-J. Lee, and S.-Y Park, ''Clause Boundary Recognition Using Support Vector Machines,'' In Proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence, pp. 505--514, 2006.", "X. Carreras and L. Marquez,''Boosting Trees for Clause Splitting,'' In Proceedings of the 5th Conference on Computational Natural Language Learning, pp. 1-3, 2001.", "A. Molina and F. Pla, ''Clause Detection using HMM,'' In Proceedings ...
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Keyword:
binaryclassification; Dependency analysis; subordinate clauses; support vector machines.
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URL: https://zenodo.org/record/1084641 https://dx.doi.org/10.5281/zenodo.1084641
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Ontology Kernel - A Convolution Kernel for Ontology Alignment
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In: http://journal.iis.sinica.edu.tw/paper/1/130648-3.pdf?cd%3D4FDE03273B6C6DD40
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Korean Compound Noun Decomposition Using Syllabic Information Only
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In: http://scai.snu.ac.kr/~scai/Publications/Journals/International/LNCS_2945_143-154(2004).pdf
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Semantic Role Determination in Korean Relative Clauses Using Idiomatic Patterns
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In: http://nova.snu.ac.kr/~sbpark/PostScript/iccpol97.ps
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16 |
Determining the Gender of Korean Names for Pronoun Generation
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In: http://www.waset.org/journals/waset/v32/v32-9.pdf
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17 |
English-Korean Machine Transliteration by Combining Statistical Model and Web Search
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In: http://www.iaeng.org/publication/IMECS2011/IMECS2011_pp15-20.pdf
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